Uplinks Schedulers for RF-Energy Harvesting Networks With Imperfect CSI

We consider a Hybrid Access Point (HAP) that is equipped with a Successive Interference Cancellation (SIC) radio, and it is responsible for charging Radio Frequency (RF) energy harvesting devices. In addition, the HAP assigns one or more uplinks data transmission slots to these devices. In this work, we address an important and challenging problem: determine an uplink transmission schedule that maximizes the throughput at the HAP. Unlike past works, we do not assume the HAP has perfect Channel State Information (CSI). We outline a discrete optimization approach that allows the HAP to learn the best transmission schedule. We also present a heuristic approach that allows the HAP to iteratively construct a schedule. Our results show that the HAP is able to learn a transmission schedule that has higher throughput than Time Division Multiple Access (TDMA) where each slot has one device.